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Pattern Recognition = 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28 – October 1, 2020, Proceedings /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Pattern Recognition/ edited by Zeynep Akata, Andreas Geiger, Torsten Sattler.
其他題名:	42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28 – October 1, 2020, Proceedings /
其他作者:	Sattler, Torsten.
面頁冊數:	XV, 490 p. 13 illus.online resource. :
Contained By:	Springer Nature eBook
標題:	Mathematics of Computing. -
電子資源:	https://doi.org/10.1007/978-3-030-71278-5
ISBN:	9783030712785

Pattern Recognition = 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28 – October 1, 2020, Proceedings /
Pattern Recognition42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28 – October 1, 2020, Proceedings /[electronic resource] :edited by Zeynep Akata, Andreas Geiger, Torsten Sattler. - 1st ed. 2021. - XV, 490 p. 13 illus.online resource. - Image Processing, Computer Vision, Pattern Recognition, and Graphics ;12544. - Image Processing, Computer Vision, Pattern Recognition, and Graphics ;9219.

Normalizing Flow, Semantics, Physics, Camera Calibration -- Characterizing The Role of A Single Coupling Layer in Affine Normalizing Flows -- Semantic Bottlenecks: Quantifying & Improving Inspectability of Deep Representations -- Bias Detection and Prediction of Mapping Errors in Camera Calibration -- Learning to Identify Physical Parameters from Video Using Differentiable Physics -- Computer Vision, Pattern Recognition, Machine Learning -- Assignment Flow For Order-Constrained OCT Segmentation -- Boosting Generalization in Bio-Signal Classification by Learning the Phase-Amplitude Coupling -- Long-Tailed Recognition Using Class-Balanced Experts -- Analyzing the Dependency of ConvNets on Spatial Information -- Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels -- Observer Dependent Lossy Image Compression -- Adversarial Synthesis of Human Pose from Text -- Long-Term Anticipation of Activities with Cycle Consistency -- Multi-Stage Fusion for One-click Segmentation -- Neural Architecture Performance Prediction Using Graph Neural Networks -- Discovering Latent Classes for Semi-Supervised Semantic Segmentation -- Riemannian SOS-Polynomial Normalizing Flows -- Automated water segmentation and river level detection on camera images using transfer learning -- Does SGD Implicitly Optimize for Smoothness -- Looking outside the box: The role of context in Random Forest based semantic segmentation of PolSAR images -- Haar Wavelet based Block Autoregressive Flows for Trajectories -- Center3D: Center-based Monocular 3D Object Detection with Joint Depth Understanding -- Constellation Codebooks for Reliable Vehicle Localization -- Towards Bounding-Box Free Panoptic Segmentation -- Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks -- Unsupervised Part Discovery by Unsupervised Disentanglement -- On the Lifted Multicut Polytope for Trees -- Conditional Invertible Neural Networks for Diverse Image-to-Image Translation -- Image Inpainting with Learnable Feature Imputation -- 4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving -- Inline Double Layer Depth Estimation with Transparent Materials -- A Differentiable Convolutional Distance Transform Layer for Improved Image Segmentation -- PET-guided Attention Network for Segmentation of Lung Tumors from PET/CT images -- Self-supervised Disentanglement of Modality-specific and Shared Factors Improves Multimodal Generative Models -- Multimodal semantic forecasting based on conditional generation of future features.

This book constitutes the refereed proceedings of the 42nd German Conference on Pattern Recognition, DAGM GCPR 2020, which took place during September 28 until October 1, 2020. The conference was planned to take place in Tübingen, Germany, but had to change to an online format due to the COVID-19 pandemic. The 34 papers presented in this volume were carefully reviewed and selected from a total of 89 submissions. They were organized in topical sections named: Normalizing Flow, Semantics, Physics, Camera Calibration and Computer Vision, Pattern Recognition, Machine Learning.

ISBN: 9783030712785

Standard No.: 10.1007/978-3-030-71278-5doiSubjects--Topical Terms:

669457
Mathematics of Computing.

LC Class. No.: Q337.5

Dewey Class. No.: 006.4

Pattern Recognition = 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28 – October 1, 2020, Proceedings /
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